Members of the ERATOSTHENES Centre of Excellence visited Tunisia to promote the current activities of the Centre, both in terms of research and business, targeting on expanding the current network of the Centre towards the implementation of the strategic planning in Eastern Mediterranean Middle East and North Africa (EMMENA) region. The mission took place between February 26, 2024, and March 1, 2024, consisting of the following members of the Centre: Prof. Andreas Anayiotos, Dr. Kyriakos Themistokelous, and Dr. Constantinos Panagiotou.
Multiple meetings with leading members of two academic institutions, particularly the National Agronomic Institute of Tunisia (INAT) and Water Research and Technology Centre (CERTE), were conducted within the framework of the Memorandum of Understandings which has been signed recently with both organizations. Bilateral meetings have been conducted with faculty members from both Tunisian organizations to identify common research areas of interest, and a draft roadmap has been agreed upon that will be implemented during the next two years.
Regarding business activities, multiple meetings have been conducted with representatives of the water and agricultural authorities at both regional (Borj Cedria and Corba) and national level, along with members of the Tunisian Union of Agriculture and Fishery. In addition, an important meeting took place at the facilities of the Regional Centre of Remote Sensing for North Africa, which is expected to facilitate the penetration of the Centre’s activities in the entire North Africa region.
During the mission, the ERATOSTHENES Centre of Excellence shared good practices and achievements with the Tunisia team, such as the capabilities and functionalities of a recently developed web-based application, called Agri-Nexus Hub, focusing on optimal irrigation management; applicability of earth observation technologies in climate change adaptation, with a special focus on water management; characterization of the chemical status of groundwater systems using stochastic interpolation methods and machine learning tools; risk assessment due to pathogen exposure via stochastic simulations, assessment of groundwater potential in terms of hydrogeological and socio-economic criteria.
